AI Anomaly Detection

AI Defect Detection puts trained vision models between the camera and the analyst, scanning every frame a mission captures for the conditions that actually cause failures: corrosion on structural steel, hairline cracks in concrete and coatings, vegetation encroaching on rights-of-way, and thermal anomalies on electrical and mechanical assets. Findings are classified by defect type and scored for severity the moment imagery comes off the drone, not weeks later when someone finally opens the folder.

Each detection is geotagged to the exact asset and location it came from, linked back to the source frame, and carried forward across missions so an analyst can see whether a defect is new, growing, or already under repair. Instead of a technician scrubbing hours of footage, the system surfaces a ranked list of what needs attention and why.